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Forecasting Quarterly Profit Growth Rate Using an Integrated Classifier

  • You-Shyang Chen
  • Ming-Yuan Hsieh
  • Ya-Ling Wu
  • Wen-Ming Wu
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 10)

Abstract

This study proposes an integrated procedure based on four components: experiential knowledge, feature selection method, rule filter, and rough set theory for forecasting quarterly profit growth rate (PGR) in the financial industry. To evaluate the proposed procedure, a called PGR dataset collected from Taiwan’s stock market in the financial holding industry is employed. The experimental results indicate that the proposed procedure surpasses the listing methods in terms of both higher accuracy and fewer attributes.

Keywords

Profit growth rate (PGR) Rough sets theory (RST) Feature selection Condorcet method 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • You-Shyang Chen
    • 1
  • Ming-Yuan Hsieh
    • 2
  • Ya-Ling Wu
    • 3
  • Wen-Ming Wu
    • 4
  1. 1.Department of Information ManagementHwa Hsia Institute of Technology
  2. 2.Department of International BusinessNational Taichung University of Education
  3. 3.Department of Applied EnglishNational Chin-Yi University of Technology
  4. 4.Department of Distribution ManagementNational Chin-Yi University of Technology

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